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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Se inicializa a simula\u00e7\u00e3o para um grupo de particulas numa dimens\u00e3o (1D). Como primeiro caso N = 9"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%run Gas.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gas_old = Gas(9)\n",
      "gas_new = Gas(9)\n",
      "gas_old.iniVel(1)\n",
      "gas_new.iniVel(1)\n",
      "gas_ini = copy.deepcopy(gas_old)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gas_ini.vec_v"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "array([[ 1.3315865 ,  0.        ,  0.        ],\n",
        "       [ 0.71527897,  0.        ,  0.        ],\n",
        "       [-1.54540029,  0.        ,  0.        ],\n",
        "       [-0.00838385,  0.        ,  0.        ],\n",
        "       [ 0.62133597,  0.        ,  0.        ],\n",
        "       [-0.72008556,  0.        ,  0.        ],\n",
        "       [ 0.26551159,  0.        ,  0.        ],\n",
        "       [ 0.10854853,  0.        ,  0.        ],\n",
        "       [ 0.00429143,  0.        ,  0.        ]])"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gas_ini.calculateEkin_n()\n",
      "gas_ini.Ekin_n.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "2.8299790945754504"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gamma  = 1.0\n",
      "Tleft  = 1.0\n",
      "Tright = 2.0\n",
      "Wrange = 1.0\n",
      "dt = 0.00001\n",
      "total_time =100000000"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "timeDim = 2000\n",
      "gasTime = GasTime(gas_old,timeDim)\n",
      "taux = total_time/timeDim"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "######\n",
      "# FIXME: Redundant two lines\n",
      "gas_old.calculateDeltas()\n",
      "gas_old.calculateForces()\n",
      "gas_old.leftHB(gamma, Tleft, Wrange)\n",
      "gas_old.rightHB(gamma, Tright, Wrange)\n",
      "for i in range(total_time):    \n",
      "    \n",
      "    gas_new.stepPosition(gas_old,dt)\n",
      "    gas_new.inBox(gas_old)\n",
      "    \n",
      "    gas_new.calculateDeltas()\n",
      "    gas_new.calculateForces()\n",
      "    gas_old.leftHB(gamma, Tleft, Wrange)\n",
      "    gas_old.rightHB(gamma, Tright, Wrange)\n",
      "    gas_new.stepVelocity(gas_old, dt)\n",
      "    \n",
      "    gas_new.calculateHalfV()\n",
      "    gas_new.calculateEkin_n()\n",
      "    gas_new.calculateEnerDensity()  # h_n\n",
      "    gas_new.calculateFluxDensity()  # j_n\n",
      "    \n",
      "    if i % taux == 0:\n",
      "        gasTime.saveMicroState(gas_new, i, dt)\n",
      "        gasTime.saveState(gas_new, i, dt)\n",
      "    \n",
      "    #save the values for the next step\n",
      "    gas_old = copy.deepcopy(gas_new)\n",
      "    \n",
      "    #plt.plot(range(len(gas_old.Ekin_n)), gas_old.Ekin_n)\n",
      "\n",
      "######\n",
      "gasTime.savetxt(\"TimeEvolution2.dat\")\n",
      "gas_end = copy.deepcopy(gas_new)\n"
     ],
     "language": "python",
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       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-41-58f59114b1ca>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0mgas_new\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstepVelocity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgas_old\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m     \u001b[0mgas_new\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalculateHalfV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m     \u001b[0mgas_new\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalculateEkin_n\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m     \u001b[0mgas_new\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalculateEnerDensity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# h_n\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/home/alfaceor/Projects/ceor-phd/GasHeatBath/Gas.py\u001b[0m in \u001b[0;36mcalculateHalfV\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    201\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    202\u001b[0m       \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 203\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhalfV\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mPhiSF\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeltaR2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msigma2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meps\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPhiLJ_rc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDrPhiLJOverr_rc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    204\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhalfV\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhalfV\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    205\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/home/alfaceor/Projects/ceor-phd/GasHeatBath/Gas.py\u001b[0m in \u001b[0;36mPhiSF\u001b[0;34m(delta_r2, sigma2, eps, rc, PhiLJ_rc, DrPhiLJOverr_rc)\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mPhiSF\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelta_r2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meps\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mPhiLJ_rc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mDrPhiLJOverr_rc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mdelta_r2\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mrc\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mPhiLJ\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelta_r2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meps\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mPhiLJ_rc\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mDrPhiLJOverr_rc\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelta_r2\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mrc\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m   \u001b[0;32melse\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gasTime.savetxt(\"TimeEvolution.dat\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "TimeEvolution.dat\n"
       ]
      }
     ],
     "prompt_number": 94
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(gasTime.time[500:1200],gasTime.Ekin_nt[500:1200])\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 97
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gasTime.Ekin_nt.mean(axis=0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 84,
       "text": [
        "array([ 0.00238017,  0.00138054,  0.00244663,  0.0024977 ,  0.00291151,\n",
        "        0.00196169,  0.00241023,  0.00200979,  0.00158597])"
       ]
      }
     ],
     "prompt_number": 84
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(range(9), gasTime.enerDenst[500:1200].mean(axis=0))\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 89
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Preciso salvar o estado do gas e para isso preciso olhar o codigo anterior"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(gasTime.enerDenst[:500,0:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 65,
       "text": [
        "500"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.savetxt(\"UltimoEstado.dat\",np.hstack((gas_end.vec_r,gas_end.vec_v)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 96
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gasTime.enerDenst[500,:].std()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 56,
       "text": [
        "0.019324180126605396"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print len(gasTime.time), len(gasTime.enerDenst), len(gasTime.fluxDenst)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "20 20 20\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "rrr=np.hstack((gasTime.time.transpose(),gasTime.enerDenst,gasTime.enerDenst))\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ValueError",
       "evalue": "all the input arrays must have same number of dimensions",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-19-1cd2d6316761>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrrr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgasTime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgasTime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menerDenst\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgasTime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menerDenst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;32m/usr/lib/python2.7/dist-packages/numpy/core/shape_base.pyc\u001b[0m in \u001b[0;36mhstack\u001b[0;34m(tup)\u001b[0m\n\u001b[1;32m    273\u001b[0m     \u001b[0;31m# As a special case, dimension 0 of 1-dimensional arrays is \"horizontal\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    274\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0marrs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 275\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_nx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    276\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    277\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0m_nx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcatenate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mValueError\u001b[0m: all the input arrays must have same number of dimensions"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gasTime.fluxDenst[0].sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "0.0"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.rc('font', size=25)\n",
      "plt.rc('text', usetex=True)\n",
      "plt.plot(gasTime.time,gasTime.fluxDenst.sum(axis=1))\n",
      "plt.xlabel(\"$t$\")\n",
      "plt.ylabel(\"$j_{tot}$\")\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 76
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.rc('font', size=25)\n",
      "plt.rc('text', usetex=True)\n",
      "plt.plot(gasTime.time,gasTime.enerDenst.sum(axis=1))\n",
      "plt.xlabel(\"$t$\")\n",
      "plt.ylabel(\"$E_{tot}$\")\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 77
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots()\n",
      "plt.title(\"$ j_{x_n} $\")\n",
      "plt.ylabel(\"$t$ steps\")\n",
      "plt.xlabel(\"$n$\")\n",
      "#plt.colorbar()\n",
      "#heatmap = ax.pcolor(enerDensTemp, cmap='RdBu')#plt.cm.Blues) #[:,1:gas_old.N-2]\n",
      "heatmap = ax.pcolor(gasTime.fluxDenst, cmap='RdBu')#plt.cm.Blues)\n",
      "fig.colorbar(heatmap)\n",
      "#plt.imshow(enerDensTemp[:,1:gas_old.N-2])\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Grafica das posi\u00e7\u00f5es das part\u00edculas"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.rc('font', size=30)\n",
      "plt.rc('text', usetex=True)\n",
      "plt.ylabel(\"$x$\")\n",
      "plt.xlabel(\"$t$\")\n",
      "for i in range(gas_old.N):\n",
      "    plt.plot(gasTime.time, gasTime.xt[:,i])\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 78
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.rc('font', size=30)\n",
      "plt.rc('text', usetex=True)\n",
      "plt.ylabel(\"$x$\")\n",
      "plt.xlabel(\"$t$\")\n",
      "plt.plot(gasTime.time, gasTime.xt[:,8],'o')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gas_ini.plot()\n",
      "gas_end.plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "gas_ini.calculateDeltas()\n",
      "gas_ini.calculateHalfV()\n",
      "gas_ini.calculateEkin_n()\n",
      "gas_ini.calculateEnerDensity()\n",
      "gas_ini.calculateFluxDensity()\n",
      "print gas_ini.fluxDensity.sum(), gas_ini.enerDensity.sum()\n",
      "print gas_end.fluxDensity.sum(), gas_end.enerDensity.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "-0.00401938256292 0.139652490695\n",
        "-0.0857579603098 0.139652490798\n"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A densidade total de energia esta se conservando. Mas o fluxo deveria ter sido zero "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fluxDensTemp.sum(axis)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 63,
       "text": [
        "0.054938355226009573"
       ]
      }
     ],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(time,fluxDensTemp)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(enerDensTemp)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 75,
       "text": [
        "100000"
       ]
      }
     ],
     "prompt_number": 75
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pode-se notar que a energia n\u00e3o esta sendo conservada o qual deveria ter acontecido para este caso. Por tanto vamos denovo passo a passo"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ejex = np.arange(0.9,3,0.01)\n",
      "ejey = np.zeros(len(ejex))\n",
      "for i in range(len(ejex)):\n",
      " ejey[i] = PhiSF((ejex[i]**2), 1.0, 0.1, 2.5, gasIni.PhiLJ_rc, gasIni.DrPhiLJOverr_rc)\n",
      "#ejey = FSFAxis(ejex,-1.0,1.0,0.1,gasIni.DrPhiLJOverr_rc)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.plot(ejex,ejey)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 37
    }
   ],
   "metadata": {}
  }
 ]
}